Data Analyst

Date: 7 May 2025

Location:

MITC, Kandivli, MITC, Kandivli, IN

Company: Mahindra & Mahindra Ltd

Responsibilities & Key Deliverables

Objective: A Data Analyst in the Data Insight and Analytics team is crucial for transforming raw data into actionable insights, enabling informed decision-making across the organization. Without this role, the company would struggle to identify trends, measure performance, and drive data-driven strategies, leading to potential inefficiencies and missed opportunities

• Identify trends and patterns in data
• Measure performance and KPIs effectively
• Drive data-driven strategies and decisions
• Optimize processes and improve operational efficiency
• Gain a competitive edge through informed insights

Data Collection and Preprocessing :
Collect data from various sources including databases, APIs, and external datasets. Clean and preprocess data to handle missing values, remove duplicates, and ensure data consistency and quality.
Exploratory Data Analysis (EDA) :
Use statistical techniques and visualization tools to explore and analyze data. Identify trends, patterns, and anomalies that can provide actionable insights.
Statistical Modeling :
Develop statistical models to test hypotheses, identify relationships between variables, and make predictions. Use techniques such as regression analysis, time series analysis, and clustering.
Machine Learning:
Implement machine learning algorithms to build predictive models. This includes supervised learning (e.g., classification, regression) and unsupervised learning (e.g., clustering, dimensionality reduction).
Cross-Functional Collaboration:
Work with different teams (e.g., marketing, finance, operations) to understand their data needs and provide insights that support their objectives.
Data Visualization :
Create interactive dashboards and reports using tools like Tableau, Power BI, or Python libraries (e.g., Matplotlib, Seaborn) to visualize data and communicate insights effectively.
Data Validation :
Ensure the accuracy and integrity of data through rigorous validation processes. This includes verifying data sources, checking for consistency, and implementing data quality controls.

Experience

3-5 years of experience in a Data Analyst role, Experience working with large datasets and performing complex data analysis.

Industry Preferred

Manufacturing - Preferably Auto & Ancillary Business

Qualifications

Bachelor's or Master's degree in Statistics/ Applied statistics

General Requirements

Technical Skills:
Proficiency in programming languages such as Python or R. Experience with data analysis libraries (e.g., Pandas, NumPy) and machine learning frameworks (e.g., Scikit-learn, TensorFlow).
Statistical Knowledge
Strong understanding of statistical methods and techniques. Experience with statistical software (e.g., SAS, SPSS) is a plus.
Data Visualization
Experience with data visualization tools and libraries. Ability to create clear and insightful visualizations.
Database Management
Knowledge of SQL and experience with database management systems (e.g., MySQL, PostgreSQL, Google Bigquery,).
Secondary Skills :

Understanding best practices and benchmarking processes in related industry

Behavioural Competencies/ Skills :

Anticipating and leveraging business opportunities
Fruitful utilisation of Resources,
Giving Customer Delight,
Excellent communication and collaboration skills.
Strong problem-solving and analytical abilities.
Ability to work independently and as part of a team.